Senior Data Scientist

Title: Senior Data Scientist (Hybrid)

Location: Columbus, OH 43219

Type: Contract approved through December 2024

Work arrangement:

Hybrid, 3 days/week onsite in Columbus OH office plus 2 days/week remote

Summary:

Our client is seeking to add a Senior Data Scientist to their Enterprise Data and Analytics. The Senior Data Scientist will leverage machine learning, segmentation, and statistical inference on huge data sets to improve how our client's understanding of their customers and the communities they serve. The Senior Data Scientist contributes to building and developing the organization's data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision-making processes.

Duties and Responsibilities:

Performs advanced analytics methods to extract value from business data.

Performs large-scale experimentation and build data-driven models to answer business questions.

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence.

Determines requirements that will be used to train and evolve deep learning models and algorithms.

Articulates a vision and roadmap for the exploitation of data as a valued corporate asset.

Influences product teams through presentation of data-based recommendations.

Evangelizes best practices to analytics and products teams.

Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring.

Performs other duties as assigned.

Basic Qualifications:

Master's Degree in computer science, statistics, economics or related fields

3+ years of work and/or educational experience in machine learning or cloud computing, experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, experience scripting languages, and packages, experience building and deploying predictive models, experience web scraping, and scalable data pipelines and experience with big data analysis tools and techniques.

Preferred Qualifications (not required):

Up-to-date knowledge of machine learning and data analytics tools and techniques

Strong knowledge in predictive modeling methodology

Experienced at leveraging both structured and unstructured data sources

Willingness and ability to learn new technologies on the job

Demonstrated ability to communicate complex results to technical and non-technical audiences

Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines

Strategic, intellectually curious thinker with focus on outcomes

Professional image with the ability to form relationships across functions

Strong experience with R/RStudio, Python, SAS, SQL, NoSQL

Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)

Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)

Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling

Financial Services background